公平硬币倾向于落在开始时的同一边:来自350,757次投掷的证据

František Bartoš, Alexandra Sarafoglou, Henrik R. Godmann, Amir Sahrani, David Klein Leunk, Pierre Y. Gui, David Voss, Kaleem Ullah, Malte J. Zoubek, Franziska Nippold, Frederik Aust, Felipe F. Vieira, Chris-Gabriel Islam, Anton J. Zoubek, Sara Shabani, Jonas Petter, Ingeborg B. Roos, Adam Finnemann, Aaron B. Lob, Madlen F. Hoffstadt, Jason Nak, Jill de Ron, Koen Derks, Karoline Huth, Sjoerd Terpstra, Thomas Bastelica5, Magda Matetovici, Vincent L. Ott, Andreea S. Zetea, Katharina Karnbach, Michelle C. Donzallaz, Arne John, Roy M. Moore, Franziska Assion, Riet van Bork, Theresa E. Leidinger, Xiaochang Zhao, Adrian Karami Motaghi, Ting Pang, Hannah Armstrong, Tianqi Peng, Mara Bialas, Joyce Y. -C. Pang, Bohan Fu, Shujun Yang, Xiaoyi Lin, Dana Sleiffer, Miklos Bognar, Balazs Aczel, Eric-Jan Wagenmakers
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引用次数: 0

摘要

很多人都扔过硬币,但很少有人停下来思考这个过程的统计和物理复杂性。在一项预先登记的研究中,我们收集了350,757次抛硬币的数据,以测试Persi Diaconis开发的人类抛硬币物理模型的反直觉预测。该模型断言,当人们抛一枚普通的硬币时,它倾向于落在开始时的同一边——迪亚康尼斯估计出现同一边结果的概率约为51%。我们的数据为这个精确的预测提供了强有力的支持:硬币往往落在同一侧,$\text{Pr}(\text{同一侧})= 0.508$,95%可信区间(CI) [$0.506$, $0.509$], $\text{BF}_{\text{同一侧偏差}}=2364$。此外,数据显示,这种同侧偏见的程度在人与人之间存在相当大的差异。我们的数据还证实了一个通用预测,即当人们投掷一枚普通的硬币时——初始面是随机确定的——它出现正面或反面的可能性是一样的:$\text{Pr}(\text{heads}) = 0.500$, 95% CI [$0.498$, $0.502$],$\text{BF}_{\text{正面-反面偏差}}= 0.183$。此外,这种正反偏差的缺失似乎在不同的硬币中并不存在。因此,我们的数据提供了强有力的证据,表明当一些(但不是全部)人抛一枚公平的硬币时,硬币往往落在开始时的同一边。我们的数据为Diaconis的抛硬币物理模型提供了令人信服的统计支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fair coins tend to land on the same side they started: Evidence from 350,757 Flips
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected 350,757 coin flips to test the counterintuitive prediction from a physics model of human coin tossing developed by Persi Diaconis. The model asserts that when people flip an ordinary coin, it tends to land on the same side it started -- Diaconis estimated the probability of a same-side outcome to be about 51%. Our data lend strong support to this precise prediction: the coins landed on the same side more often than not, $\text{Pr}(\text{same side}) = 0.508$, 95% credible interval (CI) [$0.506$, $0.509$], $\text{BF}_{\text{same-side bias}} = 2364$. Furthermore, the data revealed considerable between-people variation in the degree of this same-side bias. Our data also confirmed the generic prediction that when people flip an ordinary coin -- with the initial side-up randomly determined -- it is equally likely to land heads or tails: $\text{Pr}(\text{heads}) = 0.500$, 95% CI [$0.498$, $0.502$], $\text{BF}_{\text{heads-tails bias}} = 0.183$. Furthermore, this lack of heads-tails bias does not appear to vary across coins. Our data therefore provide strong evidence that when some (but not all) people flip a fair coin, it tends to land on the same side it started. Our data provide compelling statistical support for Diaconis' physics model of coin tossing.
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